Search: “models”

FPEdit: Robust LLM Fingerprinting through Localized Parameter Editing

arXiv:2508.02092v3 Announce Type: replace-cross Abstract: Large language models represent significant investments in computation, data, and engineering expertise, making them extraordinarily valuable

31 Jul 2026

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PRISM Edit: One Vector for All Temporal Answers

DGX agent

arXiv:2607.11327v2 Announce Type: replace-cross Abstract: Model editing keeps large language models (LLMs) up to date without retraining, but temporal facts expose a limitation of the prevailing locat

model-releasesarxiv-cs-ai

15 Jul 2026

Off-the-Shelf LLMs as Process Scorers: Training-Free Alternative to PRMs for Mathematical Reasoning

arXiv:2606.01682v1 Announce Type: cross Abstract: Selecting the best response from multiple small-model samples using a stronger scorer is a simple inference-time strategy, but fails when the small mo

2 Jun 2026

SafeGen-Bench: Benchmarking Safety in Image-Conditioned Text-to-Video Generation

model-releasesarxiv-cs-cv

arXiv:2606.01481v1 Announce Type: new Abstract: With the rapid advancements in text-to-image diffusion models, generative video models (T2V models) like Sora can now produce short synthetic videos fro

2 Jun 2026

jina-embeddings-v5-omni: Text-Geometry-Preserving Multimodal Embeddings via Frozen-Tower Composition

arXiv:2605.08384v1 Announce Type: new Abstract: In this work, we introduce frozen-encoder model composition, a novel approach to multimodal embedding models. We build on the VLM-style architecture, in

12 May 2026

A Probabilistic Consensus-Driven Approach for Robust Counterfactual Explanations

arXiv:2604.17494v1 Announce Type: new Abstract: Counterfactual explanations (CFEs) are essential for interpreting black-box models, yet they often become invalid when models are slightly changed. Exis

21 Apr 2026

ESsEN: Training Compact Discriminative Vision-Language Transformers in a Low-Resource Setting

arXiv:2604.18452v1 Announce Type: cross Abstract: Vision-language modeling is rapidly increasing in popularity with an ever expanding list of available models. In most cases, these vision-language mod

21 Apr 2026

User-Assistant Bias in LLMs

arXiv:2508.15815v3 Announce Type: replace Abstract: Modern large language models (LLMs) are typically trained and deployed using structured role tags (e.g. system, user, assistant, tool) that explicit

21 Apr 2026

SLM Finetuning for Natural Language to Domain Specific Code Generation in Production

arXiv:2604.09952v1 Announce Type: new Abstract: Many applications today use large language models for code generation; however, production systems have strict latency requirements that can be difficul

14 Apr 2026

What to Say and When to Say it: Live Fitness Coaching as a Testbed for Situated Interaction

model-releasesarxiv-cs-cv

arXiv:2407.08101v4 Announce Type: replace Abstract: Vision-language models have shown impressive progress in recent years. However, existing models are largely limited to turn-based interactions, wher

14 Apr 2026

EXAONE 4.5 Technical Report

arXiv:2604.08644v1 Announce Type: new Abstract: This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integr

13 Apr 2026

A Bayes-Markov Neuromorphic Model of Cortical Orientation Selectivity: A Computational Re-implementation and Quantitative Simulation Study

arXiv:2608.12388v1 Announce Type: cross Abstract: The emergence of orientation selectivity in the primary visual cortex (V1) remains a central question in computational neuroscience. Shirazi's Bayes-M

Are Large Language Models Reliable Reviewers? A Benchmark for Error Detection in Financial Documents

arXiv:2608.12342v1 Announce Type: new Abstract: Ensuring the accuracy of financial documents is critical for economic analysis, regulatory compliance, and corporate decision-making. Several studies ha

Are you Talking Logic to Me? Assessing Language Models Syllogistic Reasoning Capabilities

arXiv:2608.12374v1 Announce Type: cross Abstract: Language models (LMs) struggle with logical tasks like reasoning on syllogisms. It has been shown that Knowledge Representation (KR) plays a crucial r

Behavioral Reprogramming of Open-Weights Models: Cognitive Plasticity and Alignment Bounds

arXiv:2608.13069v1 Announce Type: new Abstract: Large language models (LLMs) are predominantly aligned to function as passive, sycophantic assistants. We challenge this default paradigm by empirically

FIRE-VLA: Failure-Informed Self-Evolution for Vision-Language-Action Models in Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2608.13395v1 Announce Type: new Abstract: Reinforcement learning improves autonomous-driving vision-language-action (VLA) models by evaluating trajectories sampled from the current policy. Group

Tutorials

Jointly Predicting Courses and Grades Using a Transformer-Based Model

arXiv:2608.13409v1 Announce Type: new Abstract: Existing predictive models in learning analytics often treat student academic history as a simple sequence, overlooking the concurrent nature of courses

tutorialsarxiv-cs-ai

Large Language Models Pass the History Exam But Miss the <<History>>: A Polish High School Exit Exam Matura Benchmark

arXiv:2608.12343v1 Announce Type: new Abstract: AI chatbots are widely used by students as knowledge sources, yet LLM benchmarks rarely assess interpretative historical reasoning. We evaluate eight le

Novels generated by language models show compressed formal variation

arXiv:2608.12630v1 Announce Type: cross Abstract: While large language models can generate entire novels, there is little information about the level of formal variation in their output over many gene

Personalized Scorer Modeling: A Learning-Based Framework for Deriving Robust Sleep Stage Labels from Multiple Experts

arXiv:2608.12446v1 Announce Type: cross Abstract: Sleep stage classification is important for the diagnosis and management of sleep disorders, yet most automatic staging studies evaluate models agains

Safety

Scaling Automatic Research Agents via World Models

arXiv:2608.12564v1 Announce Type: new Abstract: Automating empirical research is a long-standing direction of AI. Recent automatic research (AutoResearch) agents bring this goal within reach, as moder

safetyarxiv-cs-lg

Air Quality Station Simulation via LSTM and Attention-Based Modelling

arXiv:2608.11839v1 Announce Type: new Abstract: Poor air quality in urban areas is driven by a complex chain of processes and presents a significant public health concern. To better understand and con

Can Vision Models Read the Radar Display? On the Feasibility of Radar Imagery for Air Traffic Complexity Estimation

arXiv:2608.11810v1 Announce Type: new Abstract: Air traffic controllers perceive traffic complexity through the radar display, suggesting that a computer vision model operating on the same imagery may

researcharxiv-cs-cv

CT-DeltaBench: A Benchmark for Longitudinal 3D Medical Imaging Difference Reporting with Vision-Language Models

arXiv:2608.11534v1 Announce Type: new Abstract: In medical imaging, the clinical value of Computed Tomography (CT) lies not only in depicting current disease status, but crucially in enabling longitud

How effective are VLMs in assisting humans in inferring the quality of mental models from Multimodal short answers?

arXiv:2603.00056v2 Announce Type: replace-cross Abstract: STEM Mental models can play a critical role in assessing students' conceptual understanding of a topic. They not only offer insights into what

Orientation, not magnitude: the causal structure of task-vector interference in merged language models

arXiv:2608.11797v1 Announce Type: new Abstract: Model merging by task arithmetic works until it doesn't, and the field diagnoses why with magnitudes: layerwise representation bias, deviations from cro

Poor Man's Agentic Modeling: Simulating Large LLM-Agent Societies on a Laptop

arXiv:2608.11215v1 Announce Type: new Abstract: Simulating societies of many large language model (LLM) agents is expensive, yet the questions asked of such simulations are usually macroscopic: phase

Qwen-MusicAVQA-7B: A Multimodal Model for Music Audio-Visual QA

model-releasesarxiv-cs-cv

arXiv:2608.11329v1 Announce Type: cross Abstract: A common approach to adding audio to a vision-language model is to train or adapt a large omni-modal system. We show that a lightweight alternative ca

Semantic Lenia: Emergence of Homeostatic Solitons within the Semantic Space of Large Language Models

arXiv:2608.11657v1 Announce Type: cross Abstract: We introduce Semantic Lenia, an artificial life framework that transforms Large Language Model (LLM) inference from a static optimization problem into

Local Ai

Certify or Refuse: A Cross-Model Map for Selective Risk Control with Coverage Floors under Covariate Shift

arXiv:2608.10893v1 Announce Type: new Abstract: Certified selective predictors attain whatever coverage they attain; operators impose an automation floor: answer at least a eta-fraction of shifted tar

local-aiarxiv-cs-cl

Safety

Hidden in Plain Sight: Diffusion-Based Unrestricted Robotic Attacks on Vision-Language-Action Models

arXiv:2608.10393v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong capabilities in controlling robots across diverse manipulation tasks. However, their adversarial r

safetyarxiv-cs-ai

HQ-DM: Single Hadamard Transformation-Based Quantization-Aware Training for Low-Bit Diffusion Models

arXiv:2512.05746v3 Announce Type: replace Abstract: Diffusion models have demonstrated significant applications in the field of image generation. However, their high computational and memory costs pos

researcharxiv-cs-cv

Locally Deployable Small Language Models for Emergency Department Decision Support: A Systematic Benchmark of Fine-Tuning Strategies

arXiv:2608.10273v1 Announce Type: cross Abstract: Deploying large language models (LLMs) for decision support in emergency departments (EDs) faces two major challenges: privacy risks of transmitting p

Tutorials

ReCBM: Uncertainty-Gated Relational Reasoning for Concept Bottleneck Models

arXiv:2608.10004v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) provide an interpretable framework by grounding predictions in human-understandable concepts, enabling semantic inspect

tutorialsarxiv-cs-ai

Safety

Surgical WAM: A World-Action Model for Data-Efficient Surgical Robot Learning

arXiv:2608.11204v1 Announce Type: cross Abstract: Learning reliable surgical manipulation policies is bottlenecked by the scarcity of action-labeled demonstrations: teleoperated surgical robot (e.g.,

safetyarxiv-cs-ai

Agents

Activation Probes Surface Code-Security Signals that the Model's Output Misses

arXiv:2608.09643v1 Announce Type: cross Abstract: AI coding agents now write a growing share of production code, and human security review does not scale at the rate code is generated. The agents in w

agentsarxiv-cs-lg

An Agentic AI Framework Overcomes Fundamental Limitations of Large Language Models for Glaucoma Detection from Fundus Photography

arXiv:2608.07651v1 Announce Type: new Abstract: Large language models (LLMs) show promise in medical image interpretation but suffer from hallucination, limited accuracy, and run-to-run inconsistency.

CosmosAlign: Adapting a World Foundation Model for Generative Traffic Video Forecasting

arXiv:2608.07693v1 Announce Type: cross Abstract: Generative traffic video forecasting aims to synthesize long-horizon, temporally coherent future videos of traffic scenes from a short observation his

DialectS2S: End-to-End Speech Dialogue Modeling for Low-Resource Chinese Dialects

arXiv:2608.08067v1 Announce Type: cross Abstract: Current end-to-end speech dialogue models are primarily optimized for mainstream languages and remain limited in low-resource dialect scenarios due to

Tutorials

Ensemble learning of pathology foundation models for precision oncology

arXiv:2508.16085v2 Announce Type: replace Abstract: Histopathology is essential for cancer diagnosis and treatment selection, and pathology foundation models learn visual representations from whole-sl

tutorialsarxiv-cs-cv

FemWear: A Specialized Wearable Foundation Model for Women's Health

arXiv:2608.08244v1 Announce Type: new Abstract: General wearable foundation models are pretrained across broad sensor streams and populations, but are not designed around women's-health tasks. We intr

FitAQA: A Benchmark of Fitness Action Quality Assessment for Multimodal Large Language Models

arXiv:2608.08736v1 Announce Type: new Abstract: Fitness Action Quality Assessment (AQA) is important for intelligent sports training, yet the capabilities of Multimodal Large Language Models (MLLMs) i

From Independent to Correlated Diffusion: Generalized Generative Modeling with Probabilistic Computers

arXiv:2603.27996v2 Announce Type: replace Abstract: Diffusion models have emerged as a powerful framework for generative tasks in deep learning. They decompose generative modeling into two computation

researcharxiv-cs-lg

Fusion Training for Mathematical Generalization in Large Language Models

arXiv:2608.09893v1 Announce Type: cross Abstract: Thinking Mode Fusion (TMF) enables large language models to support both concise responses and long-form reasoning by unifying a non-thinking mode and

Local Ai

GWM-VLA: Geometry-Aware Latent World Modeling for Vision-Language-Action Learning

arXiv:2608.07619v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models achieve strong robotic manipulation performance but often degrade under visual and environmental shifts. Latent worl

local-aiarxiv-cs-ro

MoE-Prism: Disentangling Monolithic Experts for Elastic MoE Services via Model-System Co-Designs

arXiv:2510.19366v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) scales model capacity through sparse activation, and is becoming an important architecture for large language models (LLMs)

researcharxiv-cs-cl

MonitorBench: A Comprehensive Benchmark for Chain-of-Thought Monitorability in Large Language Models

arXiv:2603.28590v3 Announce Type: replace Abstract: Large language models (LLMs) can generate chains of thought (CoTs) that are not always causally responsible for their final outputs. When such a mis

Omni2LoRA: Coherence-Preserving Parametric Memory for Efficient Omni Language Models

arXiv:2608.09227v1 Announce Type: new Abstract: Omnimodal language models (OLMs) enable unified audio-visual understanding, but processing long joint token sequences makes inference computationally pr